Identifying the best performers from the 200 wheat lines based on heat tolerance of leaf carbon exchange
GRDC Heat Tolerance Project
Report ID: 2024-01-01
The performances of the wheat lines are presented based on the single-trial, single-trait analysis of the 2023 screening data of photosynthesis, respiration and Tcrit.
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| Abbreviation | Description |
|---|---|
| °C | Degree Celsius |
| AAGI | Analytics for the Australian Grains Industry |
| GEBV | Genomic Breeding Values |
| GRDC | Grains Research and Development Corporation |
| Tcrit | Critical temperature of Photosystem II disruption |
| TOS | Time of sowing |
1 Overview
GRDC Heat Tolerance project aims to identify wheat lines that have higher heat tolerance of leaf carbon exchange. An experiment was conducted with approximately 200 wheat lines screened for multiple traits (of which photosynthesis, respiration and Tcrit were of interest) at multiple locations with up to two TOS. The aim of this report is to provide the GEBV per trial as well as overall GEBV for each trait to advise the University of Sydney and Intergrain for their field trials in 2024.
2 Data description
The data used in this report originates from the 2023 field trials conducted in four sites (Griffith, Merredin, Narrabri and Parkes) with one or two sowing times (referred to as TOS1 and TOS2 hereafter) in Australia. In this report, the combination of site location and TOS is referred to as a trial. In total, there were six trials as listed in Table 1.
| Trial | Photosynthesis | Respiration | Tcrit |
|---|---|---|---|
| Griffiths TOS2 | |||
| Merredin TOS1 | X | ||
| Merredin TOS2 | X | ||
| Narrabri TOS1 | |||
| Narrabri TOS2 | |||
| Parkes TOS1 |
2.1 Genotype
In this report, the term genotype is used synonymously as line. The experiment involved a total of 203 wheat genotypes with every trial sowing approximately 200 genotypes. Almost all genotypes were sowed at each trial (see Table 2, Table 3, and Table 4 for the genotype concurrence across trials for photosynthesis, respiration and Tcrit, respectively). Note that the Tcrit was not screened at Merredin.
| Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 | |
|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 199 | 199 | 199 | 194 | 193 | 186 |
| Merredin TOS1 23 | 199 | 199 | 199 | 194 | 193 | 186 |
| Merredin TOS2 23 | 199 | 199 | 199 | 194 | 193 | 186 |
| Narrabri TOS1 23 | 194 | 194 | 194 | 198 | 197 | 182 |
| Narrabri TOS2 23 | 193 | 193 | 193 | 197 | 197 | 181 |
| Parkes TOS1 23 | 186 | 186 | 186 | 182 | 181 | 186 |
| Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 | |
|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 199 | 199 | 199 | 194 | 194 | 199 |
| Merredin TOS1 23 | 199 | 199 | 199 | 194 | 194 | 199 |
| Merredin TOS2 23 | 199 | 199 | 199 | 194 | 194 | 199 |
| Narrabri TOS1 23 | 194 | 194 | 194 | 198 | 198 | 194 |
| Narrabri TOS2 23 | 194 | 194 | 194 | 198 | 198 | 194 |
| Parkes TOS1 23 | 199 | 199 | 199 | 194 | 194 | 199 |
| Griffith TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 | |
|---|---|---|---|---|
| Griffith TOS2 23 | 199 | 194 | 194 | 198 |
| Narrabri TOS1 23 | 194 | 198 | 198 | 193 |
| Narrabri TOS2 23 | 194 | 198 | 198 | 193 |
| Parkes TOS1 23 | 198 | 193 | 193 | 198 |
2.2 Traits
There were many traits recorded, however, the focus of this report is the three physiological traits of interest: photosynthesis, respiration and Tcrit. None of these traits are directly observed; the traits of interest are all estimated from the raw data measured by the instruments in the second phase of the experiment. It should be noted that there are different ways of estimating and calibrating these traits, thus multiple measurements are recorded for each trait. The measurement used in the data sheet is given in Table 5.
| Trait | Code | Desired | |
|---|---|---|---|
| Photosynthesis | AMaxAreaRaw |
High | |
| Respiration | RespirationAreaAdjSloRan |
Low | |
| Tcrit | Tcrit |
High |
A sample reading from the instruments are shown in Figure 1. For photosynthesis, the values are read at the start and end times with temperature kept at 35°C and the slope from the connection of the two points is used to estimate the photosynthesis. For respiration, the slope of the linear model fitted to the reading of the instrument over time since 1 hour of the instrument is in operation. This slope is converted to a respiration area. For Tcrit, the fluorescence value is read across varying temperature and a break point analysis is used to estimate the temperature at which the fluorescence value changes suddenly. All the processing of the raw instrument data to phenotype data was conducted by Dr. Andrew Scafaro.
2.3 Multi-phase experimental structure
There were two phases in the experiment: the field phase followed by screening phase. Both phases followed the experimental design provided by AAGI with appropriate randomisation and replication. The field phase involved sowing of wheat genotypes with one or two replicates (inadvertently, there were some that had three or four replicates due to renaming of genotypes as discussed in Section 7.2). Table 6, Table 7, and Table 8 show the genotype replications in the field phase for photosynthesis, respiration and Tcrit, respectively.
| Trial | One replicate | Two replicates | Three replicates | Four replicates | Total number of plots |
|---|---|---|---|---|---|
| Griffith TOS2 23 | 100 | 98 | 0 | 1 | 300 |
| Merredin TOS1 23 | 100 | 98 | 0 | 1 | 300 |
| Merredin TOS2 23 | 99 | 99 | 1 | 0 | 300 |
| Narrabri TOS1 23 | 0 | 196 | 0 | 2 | 400 |
| Narrabri TOS2 23 | 10 | 185 | 0 | 2 | 388 |
| Parkes TOS1 23 | 105 | 80 | 0 | 1 | 269 |
| Trial | One replicate | Two replicates | Three replicates | Four replicates | Total number of plots |
|---|---|---|---|---|---|
| Griffith TOS2 23 | 100 | 98 | 0 | 1 | 300 |
| Merredin TOS1 23 | 100 | 98 | 0 | 1 | 300 |
| Merredin TOS2 23 | 99 | 99 | 1 | 0 | 300 |
| Narrabri TOS1 23 | 0 | 196 | 0 | 2 | 400 |
| Narrabri TOS2 23 | 0 | 196 | 0 | 2 | 400 |
| Parkes TOS1 23 | 100 | 98 | 0 | 1 | 300 |
| Trial | One replicate | Two replicates | Four replicates | Total number of plots |
|---|---|---|---|---|
| Griffith TOS2 23 | 100 | 98 | 1 | 300 |
| Narrabri TOS1 23 | 0 | 196 | 2 | 400 |
| Narrabri TOS2 23 | 0 | 196 | 2 | 400 |
| Parkes TOS1 23 | 99 | 98 | 1 | 299 |
The screening phase involved taking the leaves from the field plot and laying it out onto the plate to measure with instruments. The total number of days, the number of plates and the dimension of the plate along with the information of replication (either at field or screening phase) by trial is shown in Table 9, Table 10, and Table 11 for photosynthesis, respiration and Tcrit, respectively.
| Trial | Days | Plates | Rows | Columns | Field | Screening | Plots | Observations |
|---|---|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 3 | 6 | 6 | 4 | 1 | 1 | 55 | 396 |
| 2 | 45 | |||||||
| 2 | 1 | 146 | ||||||
| 2 | 50 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 1 | |||||||
| Merredin TOS1 23 | 3 | 6 | 6 | 4 | 1 | 1 | 55 | 396 |
| 2 | 45 | |||||||
| 2 | 1 | 146 | ||||||
| 2 | 50 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 1 | |||||||
| Merredin TOS2 23 | 3 | 6 | 6 | 4 | 1 | 1 | 53 | 396 |
| 2 | 46 | |||||||
| 2 | 1 | 149 | ||||||
| 2 | 49 | |||||||
| 3 | 1 | 2 | ||||||
| 2 | 1 | |||||||
| Narrabri TOS1 23 | 5 | 6 | 6 | 4 | 2 | 1 | 138 | 660 |
| 2 | 254 | |||||||
| 4 | 1 | 2 | ||||||
| 2 | 6 | |||||||
| Narrabri TOS2 23 | 5 | 6 | 6 | 4 | 1 | 1 | 2 | 616 |
| 2 | 8 | |||||||
| 2 | 1 | 154 | ||||||
| 2 | 216 | |||||||
| 4 | 1 | 4 | ||||||
| 2 | 4 | |||||||
| Parkes TOS1 23 | 3 | 6 | 6 | 4 | 1 | 1 | 66 | 340 |
| 2 | 39 | |||||||
| 2 | 1 | 128 | ||||||
| 2 | 32 | |||||||
| 4 | 1 | 4 |
| Trial | Days | Plates | Rows | Columns | Field | Screening | Plots | Observations |
|---|---|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 3 | 3 | 6 | 8 | 1 | 1 | 55 | 396 |
| 2 | 45 | |||||||
| 2 | 1 | 146 | ||||||
| 2 | 50 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 1 | |||||||
| Merredin TOS1 23 | 3 | 3 | 6 | 8 | 1 | 1 | 56 | 393 |
| 2 | 44 | |||||||
| 2 | 1 | 148 | ||||||
| 2 | 48 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 1 | |||||||
| Merredin TOS2 23 | 3 | 3 | 6 | 8 | 1 | 1 | 53 | 396 |
| 2 | 46 | |||||||
| 2 | 1 | 149 | ||||||
| 2 | 49 | |||||||
| 3 | 1 | 2 | ||||||
| 2 | 1 | |||||||
| Narrabri TOS1 23 | 5 | 3 | 6 | 8 | 2 | 1 | 138 | 660 |
| 2 | 254 | |||||||
| 4 | 1 | 2 | ||||||
| 2 | 6 | |||||||
| Narrabri TOS2 23 | 5 | 3 | 6 | 8 | 2 | 1 | 137 | 660 |
| 2 | 255 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 5 | |||||||
| Parkes TOS1 23 | 3 | 3 | 6 | 8 | 1 | 1 | 52 | 396 |
| 2 | 48 | |||||||
| 2 | 1 | 148 | ||||||
| 2 | 48 | |||||||
| 4 | 1 | 4 |
| Trial | Days | Plates | Rows | Columns | Field | Screening | Plots | Observations |
|---|---|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 3 | 3 | 6 | 8 | 1 | 1 | 55 | 396 |
| 2 | 45 | |||||||
| 2 | 1 | 146 | ||||||
| 2 | 50 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 1 | |||||||
| Narrabri TOS1 23 | 5 | 3 | 6 | 8 | 2 | 1 | 138 | 660 |
| 2 | 254 | |||||||
| 4 | 1 | 2 | ||||||
| 2 | 6 | |||||||
| Narrabri TOS2 23 | 5 | 3 | 6 | 8 | 2 | 1 | 137 | 660 |
| 2 | 255 | |||||||
| 4 | 1 | 3 | ||||||
| 2 | 5 | |||||||
| Parkes TOS1 23 | 3 | 3 | 6 | 8 | 1 | 1 | 53 | 391 |
| 2 | 46 | |||||||
| 2 | 1 | 150 | ||||||
| 2 | 46 | |||||||
| 4 | 1 | 4 |
2.4 Phenotype distribution
Figure 2 shows the phenotype distribution of photosynthesis, respiration, and Tcrit as measured by coded variable in brackets by trial. The distribution of photosynthesis and respiration are skewed to the right while the distribution of Tcrit is skewed to the left. The distribution of photosynthesis is similar across trials.
| File name | Last modified |
|---|---|
| Mer_TOS1_23_Q2_Respiration.xlsx | 2023-12-21 09:34:50 |
| Mer_TOS1_23_Q2_Photosynthesis.xlsx | 2023-12-21 09:36:17 |
| Mer_TOS2_23_Q2_Respiration.xlsx | 2023-12-21 09:37:15 |
| Mer_TOS2_23_Q2_Photosynthesis.xlsx | 2023-12-21 09:37:54 |
| Nar_TOS1_23_Q2_Respiration.xlsx | 2023-12-21 09:40:10 |
| Nar_TOS1_23_Q2_Photosynthesis.xlsx | 2023-12-21 09:40:51 |
| Nar_TOS2_23_Q2_Respiration.xlsx | 2023-12-21 09:41:33 |
| Par_TOS1_23_Q2_Photosynthesis.xlsx | 2023-12-22 09:39:19 |
| NAR_TOS1_23_Tcrit.xlsx | 2023-12-22 09:49:25 |
| NAR_TOS2_23_Tcrit.xlsx | 2023-12-22 09:52:45 |
| Gri_TOS2_23_Q2_Photosynthesis.xlsx | 2024-01-02 13:47:44 |
| Nar_TOS2_23_Q2_Photosynthesis.xlsx | 2024-01-03 11:11:17 |
| GRI_TOS2_23_Tcrit.xlsx | 2024-01-05 13:56:17 |
| PAR_TOS1_23_Tcrit.xlsx | 2024-01-08 16:29:43 |
| PAR_TOS1_23_Q2_Respiration.xlsx | 2024-01-10 14:18:55 |
| Gri_TOS2_23_Q2_Respiration.xlsx | 2024-01-10 15:47:08 |
3 Statistical methods
The trait of interest is analysed using a linear mixed model using ASReml-R version 4.2.0.267 (Butler et al. 2023).
The models fitted are equivalent to single trial baseline analysis for each trait. The genotype performance prediction does not borrow information across trials, nor is the data analysed using a multi-trait model, which can also potentially improve the prediction if the traits are correlated. The residual plots suggest that not all unexplained variation is explained in the model. This effects the calculations of the standard error in the prediction and the estimates of heritability, so some caution should be taken into account in its interpretation.
The following tabs show the fitted models for each trait and the corresponding estimated variance components in Table 13, Table 14, and Table 15. The heritability for each trait by trial is estimated as
\[\frac{\sigma^2_g}{\sigma^2_g + \sigma^2}\] where \(\sigma^2_g\) is the variance component estimate for the Genotype term and \(\sigma^2\) is the residual variance. The heritability estimates are shown in the Genotype row in the Table 13, Table 14, and Table 15. Note that there are other (and likely better) ways of estimating heritability (see Piepho and Möhring 2007).
asreml(fixed = AMaxAreaRaw ~ site, random = ~diag(site):PlotRow +
diag(site):PlotRange + diag(site):Day + diag(site):Plate +
diag(site):Day:Plate + diag(site):Day:Plate:PCol + diag(site):Day:Plate:PRow +
diag(site):Day:Plate + diag(site):PlotRow:PlotRange + diag(site):Genotype,
residual = ~dsum(~units | site), data = photosynthesisII)
| Terms | Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 |
|---|---|---|---|---|---|---|
| Day | 0.378 (0.775) | 1.928 (2.156) | 1.781 (1.606) | 0.550 (0.637) | ||
| Plate | 0.291 (0.711) | 0.018 (0.350) | 0.751 (0.585) | |||
| Day:Plate | 1.508 (0.967) | 1.182 (0.980) | 0.676 (0.603) | 2.084 (0.802) | 1.803 (0.731) | |
| PlotRange | 0.027 (0.237) | 0.513 (0.487) | 0.500 (0.465) | 0.041 (0.166) | ||
| PlotRow | 0.504 (0.284) | 0.231 (0.324) | 0.858 (0.534) | |||
| Day:Plate:PCol | 1.128 (0.740) | 0.836 (0.721) | 1.566 (0.500) | 0.000 (0.360) | ||
| Day:Plate:PRow | 1.825 (0.887) | 0.374 (0.759) | ||||
| Genotype | 2.570 (1.361) Heritability: 21.0% | 2.135 (1.172) Heritability: 18.1% | 0.541 (0.430) Heritability: 5.3% | 1.560 (0.722) Heritability: 13.9% | 0.380 (1.014) Heritability: 3.8% | |
| PlotRow:PlotRange | 0.858 (1.929) | 1.278 (1.679) | ||||
| Residual | 10.721 (1.774) | 13.235 (1.613) | 4.659 (0.540) | 15.198 (1.049) | 17.129 (1.564) | 9.648 (0.824) |
asreml(fixed = RespirationAreaAdjSloRan ~ site, random = ~diag(site):PlotRow +
diag(site):PlotRange + diag(site):Day + diag(site):Plate +
diag(site):Day:Plate + diag(site):Day:Plate:PCol + diag(site):Day:Plate:PRow +
diag(site):PlotRow:PlotRange + diag(site):Genotype, residual = ~dsum(~units |
site), data = respirationII)
| Terms | Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 |
|---|---|---|---|---|---|---|
| Plate | 0.823 (0.912) | 0.000 (0.002) | ||||
| Day | 0.009 (0.010) | 0.094 (0.096) | 0.001 (0.008) | 0.032 (0.037) | 0.201 (0.203) | |
| Day:Plate | 0.000 (0.001) | 0.002 (0.004) | 0.015 (0.012) | 0.052 (0.026) | 0.001 (0.003) | |
| PlotRange | 0.000 (0.001) | 0.025 (0.010) | 0.001 (0.001) | |||
| PlotRow | 0.000 (0.001) | 0.002 (0.119) | 0.005 (0.007) | |||
| Day:Plate:PRow | 0.457 (0.185) | 0.011 (0.003) | ||||
| Day:Plate:PCol | 0.000 (0.002) | 0.008 (0.008) | 0.924 (0.263) | 0.029 (0.012) | 0.002 (0.001) | |
| Genotype | 0.004 (0.003) Heritability: 19.1% | 0.010 (0.012) Heritability: 34.2% | 0.154 (0.418) Heritability: 89.4% | 0.005 (0.016) Heritability: 20.6% | 0.037 (0.015) Heritability: 67.0% | 0.001 (0.003) Heritability: 5.3% |
| PlotRow:PlotRange | 0.190 (0.631) | 0.041 (0.026) | 0.009 (0.020) | 0.008 (0.004) | ||
| Residual | 0.042 (0.004) | 0.173 (0.018) | 2.782 (0.504) | 0.255 (0.024) | 0.227 (0.019) | 0.018 (0.003) |
asreml(fixed = Tcrit ~ site, random = ~diag(site):PlotRow + diag(site):PlotRange +
diag(site):Day + diag(site):Plate + diag(site):Day:Plate +
diag(site):Day:Plate:PCol + diag(site):Day:Plate:PRow + diag(site):PlotRow:PlotRange +
diag(site):Genotype, residual = ~dsum(~units | site), data = fluorometerII)
| Terms | Griffith TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 |
|---|---|---|---|---|
| Plate | 1.133 (1.217) | 0.547 (0.673) | 0.385 (0.725) | |
| Day | 0.001 (0.127) | 0.587 (0.519) | ||
| Day:Plate | 0.294 (0.189) | 0.384 (0.209) | 0.587 (0.255) | 0.380 (0.566) |
| PlotRow | 0.012 (0.024) | |||
| PlotRange | 0.034 (0.029) | |||
| Day:Plate:PRow | 0.060 (0.043) | 0.022 (0.032) | 0.060 (0.037) | |
| Day:Plate:PCol | 0.027 (0.036) | 2.722 (0.826) | ||
| Genotype | 0.135 (0.054) Heritability: 1.7% | 0.023 (0.061) Heritability: 0.3% | 2.327 (1.080) Heritability: 23.0% | |
| PlotRow:PlotRange | 0.241 (0.105) | 0.116 (1.544) | ||
| Residual | 0.996 (0.080) | 1.085 (0.082) | 0.960 (0.093) | 7.810 (1.355) |
The GEBV is calculated by using the prediction of genotype and trial combination for each of the trait as per Welham et al. (2004). If there were no measurable genotype variance for the trait then no GEBV is given.
The ratio of photosynthesis over respiration is predicted using the GEBV of photosynthesis and respiration. The standard error of the ratio is calculated using the delta method.
The overall GEBV for each trait is calculated by using the inverse-variance weighting (the weighted average of the GEBV across trials where weight corresponds to the inverse of the variance of the GEBV). The corresponding standard error was estimated assuming that the standard errors of the GEBV are known. This means that the standard error of the overall GEBV is likely underestimated.
4 Key results
The results are presented as either interactive plots or interactive table for GEBV by trial and for overall GEBV. The link to download the results as CSV are provided below.
4.1 GEBV by trial
Figure 3 shows visually the GEBV by trial along with the trait information. The most desired genotypes would be the points residing in the top left quadrant of most plots that is yellowish in color (of which there are not many) with a large size. There is no clear stable, stand-out performers.
The results of GEBV by trial, seen in Table 16, can be downloaded from the link below.
Download CSV for GEBV by trial
4.2 Overall GEBV
Figure 4 shows the overall GEBV in a style similar to Figure 3. The overall trait GEBV against its rank is shown in Figure 5.
The results of overall GEBV, seen in Table 17, can be downloaded from the link below.
The standard error of the overall GEBV for respiration is noticeably very high. This is possibly due to the unreliableness of this measure.
5 Conclusion
Every effort is made to make the results (including numerical results in the inline text) reproducible, but the results can change when there is an update to the data. For this reason, I recommend checking Table 12 to check the last modified date of the data files.
Due to lack of time and capacity, as mentioned in Section 3, the models fitted are equivalent to single trial baseline analysis for each trait. The genotype performance prediction does not borrow information across trials, nor is the data analysed using a multi-trait model, which can also potentially improve the prediction if the traits are correlated. The residual plots suggest that not all unexplained variation is explained in the model. This effects the calculations of the standard error in the prediction and the estimates of heritability, so some caution should be taken into account in its interpretation.
If an appropriate factor analytic mixed model for the multi-environmental trial was fitted, the method in Smith and Cullis (2018) may be a better approach to calculating the overall GEBV.
6 Acnowledgements
Many thanks to Andrew Bowerman, Andrew Scafaro and Frederike Stock for answering all my questions related to the data.
This report is written reproducibly using Quarto. For the details of the computational tools used, see Section 7.5.
7 Appendix
7.1 Original experimental design
Due to the renaming of genotypes and removal of data points, the number of genotype replications across different phases of the experiment is now different. In the original experimental design, there were exactly 200 genotypes per trial (Table 18) and exactly half of the genotype were replicated once while the other half twice in the field phase, except Narrabri where all genotypes were replicated twice (Table 19).
| Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 | |
|---|---|---|---|---|---|---|
| Griffith TOS2 23 | 200 | 200 | 200 | 191 | 191 | 200 |
| Merredin TOS1 23 | 200 | 200 | 200 | 191 | 191 | 200 |
| Merredin TOS2 23 | 200 | 200 | 200 | 191 | 191 | 200 |
| Narrabri TOS1 23 | 191 | 191 | 191 | 200 | 200 | 191 |
| Narrabri TOS2 23 | 191 | 191 | 191 | 200 | 200 | 191 |
| Parkes TOS1 23 | 200 | 200 | 200 | 191 | 191 | 200 |
| Trial | One replicate | Two replicates | Total number of plots |
|---|---|---|---|
| Griffith TOS2 23 | 100 | 100 | 300 |
| Merredin TOS1 23 | 100 | 100 | 300 |
| Merredin TOS2 23 | 100 | 100 | 300 |
| Narrabri TOS1 23 | 0 | 200 | 400 |
| Narrabri TOS2 23 | 0 | 200 | 400 |
| Parkes TOS1 23 | 100 | 100 | 300 |
7.2 Renaming of genotype names
Upon clarification with data custodians, there were some genotypes that should have been encoded differently. The renaming of the genotypes upon this clarification is listed in Table 20.
| Old name | New name |
|---|---|
| IG-ANU-HeatLine-028-2 | IG-ANU-HeatLine-028 |
| IG-ANU-HeatLine-028-1 | IG-ANU-HeatLine-028 |
| ZWB13-171-1 | ZWB13-171 |
| ZWB13-171-2 | ZWB13-171 |
| ZWW10-080-1 | ZWW10-080 |
| ZWW10-080-2 | ZWW10-080 |
7.3 Removed data points
The following data points were removed due to actual or potential data quality issues. These include the following issues for photosynthesis as reported by Dr. Andrew Scafaro:
- Narrabri TOS2, Day 2, Plates 1 and 2, 25°C and 35°C (lights not turned off during measurement which led to incorrect fluorophore reading).
- Parkes TOS1, Day 1, Plates 1 and 2, 35°C, Plate Column 4 only (instrument malfunctioned and did not read the last column of the 35 bay for this run).
- Parkes TOS1, Day 3, Plates 3 and 4, 25°C and 35°C (data was lost).
In addition to above, I eye-balled the visualisation of all the raw data and deemed some to be unreliable. The full list of remove data points are listed in Table 21.
7.4 Genotypes not present in all trials
Table 22 lists the genotypes that are absent in a subset of trials.
| Genotype | Griffith TOS2 23 | Merredin TOS1 23 | Merredin TOS2 23 | Narrabri TOS1 23 | Narrabri TOS2 23 | Parkes TOS1 23 |
|---|---|---|---|---|---|---|
| Jillaroo | X | X | ||||
| IG-ANU-HeatLine-115 | X | X | ||||
| IG-ANU-HeatLine-114 | X | X | ||||
| Brumby | X | X | ||||
| IG-ANU-HeatLine-113 | X | X | ||||
| Alatheer-4 | X | X | X | X | ||
| Shamiekh-3 | X | X | X | X | ||
| ISR812.8/CARINYA | X | X | X | X | ||
| PBI16C001-0C-0N-0N-010N-12N | X | X | X | X |
7.5 Computational tools
This report was written using Quarto version 1.4.502. The analysis was conducted using R and numerous R packages. The versions of the tools used are shown below.
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.3.1 (2023-06-16)
os macOS Sonoma 14.2.1
system aarch64, darwin20
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Australia/Sydney
date 2024-01-15
pandoc 3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
archive 1.1.7 2023-12-11 [1] CRAN (R 4.3.1)
askpass 1.2.0 2023-09-03 [1] CRAN (R 4.3.0)
asreml * 4.2.0.267 2023-07-05 [1] local
beeswarm * 0.4.0 2021-06-01 [1] CRAN (R 4.3.0)
bit 4.0.5 2022-11-15 [1] CRAN (R 4.3.0)
bit64 4.0.5 2020-08-30 [1] CRAN (R 4.3.0)
bslib 0.6.1 2023-11-28 [1] CRAN (R 4.3.1)
cachem 1.0.8 2023-05-01 [1] CRAN (R 4.3.0)
cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.3.0)
cli 3.6.2 2023-12-11 [1] CRAN (R 4.3.1)
codetools 0.2-19 2023-02-01 [1] CRAN (R 4.3.1)
colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
commonmark 1.9.0 2023-03-17 [1] CRAN (R 4.3.0)
crayon 1.5.2 2022-09-29 [1] CRAN (R 4.3.0)
crosstalk 1.2.1 2023-11-23 [1] CRAN (R 4.3.1)
data.table 1.14.10 2023-12-08 [1] CRAN (R 4.3.1)
digest 0.6.33 2023-07-07 [1] CRAN (R 4.3.0)
dplyr * 1.1.4 2023-11-17 [1] CRAN (R 4.3.1)
DT * 0.31 2023-12-09 [1] CRAN (R 4.3.1)
ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.3.0)
evaluate 0.23 2023-11-01 [1] CRAN (R 4.3.1)
expm 0.999-9 2024-01-11 [1] CRAN (R 4.3.1)
fansi 1.0.6 2023-12-08 [1] CRAN (R 4.3.1)
farver 2.1.1 2022-07-06 [1] CRAN (R 4.3.0)
fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.0)
forcats * 1.0.0 2023-01-29 [1] CRAN (R 4.3.0)
generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
ggplot2 * 3.4.4 2023-10-12 [1] CRAN (R 4.3.1)
ggtext * 0.1.2 2023-11-15 [1] Github (wilkelab/ggtext@c519337)
glue 1.6.2 2022-02-24 [1] CRAN (R 4.3.0)
gridtext 0.1.5 2022-09-16 [1] CRAN (R 4.3.0)
gtable 0.3.4 2023-08-21 [1] CRAN (R 4.3.0)
highr 0.10 2022-12-22 [1] CRAN (R 4.3.0)
hms 1.1.3 2023-03-21 [1] CRAN (R 4.3.0)
htmltools 0.5.7 2023-11-03 [1] CRAN (R 4.3.1)
htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.3.1)
httpuv 1.6.13 2023-12-06 [1] CRAN (R 4.3.1)
httr 1.4.7 2023-08-15 [1] CRAN (R 4.3.0)
jquerylib 0.1.4 2021-04-26 [1] CRAN (R 4.3.0)
jsonlite 1.8.8 2023-12-04 [1] CRAN (R 4.3.1)
kableExtra * 1.3.4 2021-02-20 [1] CRAN (R 4.3.0)
knitr 1.45 2023-10-30 [1] CRAN (R 4.3.1)
labeling 0.4.3 2023-08-29 [1] CRAN (R 4.3.0)
later 1.3.2 2023-12-06 [1] CRAN (R 4.3.1)
lattice 0.22-5 2023-10-24 [1] CRAN (R 4.3.1)
lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.3.0)
lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.3.1)
lubridate * 1.9.3 2023-09-27 [1] CRAN (R 4.3.1)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
markdown 1.12 2023-12-06 [1] CRAN (R 4.3.1)
Matrix * 1.6-4 2023-11-30 [1] CRAN (R 4.3.1)
mgcv 1.9-1 2023-12-21 [1] CRAN (R 4.3.1)
mime 0.12 2021-09-28 [1] CRAN (R 4.3.0)
msm * 1.7.1 2023-11-23 [1] CRAN (R 4.3.1)
munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
mvtnorm 1.2-4 2023-11-27 [1] CRAN (R 4.3.1)
nlme 3.1-164 2023-11-27 [1] CRAN (R 4.3.1)
openssl 2.1.1 2023-09-25 [1] CRAN (R 4.3.1)
patchwork * 1.1.3 2023-08-14 [1] CRAN (R 4.3.0)
pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
plotly * 4.10.3 2023-10-21 [1] CRAN (R 4.3.1)
processx 3.8.3 2023-12-10 [1] CRAN (R 4.3.1)
promises 1.2.1 2023-08-10 [1] CRAN (R 4.3.0)
ps 1.7.5 2023-04-18 [1] CRAN (R 4.3.0)
purrr * 1.0.2 2023-08-10 [1] CRAN (R 4.3.0)
quarto 1.3 2023-09-19 [1] CRAN (R 4.3.1)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
RColorBrewer 1.1-3 2022-04-03 [1] CRAN (R 4.3.0)
Rcpp 1.0.11 2023-07-06 [1] CRAN (R 4.3.0)
readr * 2.1.4 2023-02-10 [1] CRAN (R 4.3.0)
readxl * 1.4.3 2023-07-06 [1] CRAN (R 4.3.0)
rlang * 1.1.2 2023-11-04 [1] CRAN (R 4.3.1)
rmarkdown 2.25 2023-09-18 [1] CRAN (R 4.3.1)
rstudioapi 0.15.0 2023-07-07 [1] CRAN (R 4.3.0)
rvest 1.0.3 2022-08-19 [1] CRAN (R 4.3.0)
sass 0.4.8 2023-12-06 [1] CRAN (R 4.3.1)
scales 1.3.0 2023-11-28 [1] CRAN (R 4.3.1)
sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
shiny 1.8.0 2023-11-17 [1] CRAN (R 4.3.1)
stringi 1.8.3 2023-12-11 [1] CRAN (R 4.3.1)
stringr * 1.5.1 2023-11-14 [1] CRAN (R 4.3.1)
survival 3.5-7 2023-08-14 [1] CRAN (R 4.3.0)
svglite 2.1.3 2023-12-08 [1] CRAN (R 4.3.1)
systemfonts 1.0.5 2023-10-09 [1] CRAN (R 4.3.1)
tibble * 3.2.1 2023-03-20 [1] CRAN (R 4.3.0)
tidyr * 1.3.0 2023-01-24 [1] CRAN (R 4.3.0)
tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.3.0)
tidyverse * 2.0.0 2023-02-22 [1] CRAN (R 4.3.0)
timechange 0.2.0 2023-01-11 [1] CRAN (R 4.3.0)
tzdb 0.4.0 2023-05-12 [1] CRAN (R 4.3.0)
utf8 1.2.4 2023-10-22 [1] CRAN (R 4.3.1)
vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.3.1)
vipor 0.4.7 2023-12-18 [1] CRAN (R 4.3.1)
viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.3.0)
vroom 1.6.5 2023-12-05 [1] CRAN (R 4.3.1)
webshot 0.5.5 2023-06-26 [1] CRAN (R 4.3.0)
withr 2.5.2 2023-10-30 [1] CRAN (R 4.3.1)
xfun 0.41 2023-11-01 [1] CRAN (R 4.3.1)
xml2 1.3.6 2023-12-04 [1] CRAN (R 4.3.1)
xtable 1.8-4 2019-04-21 [1] CRAN (R 4.3.0)
yaml 2.3.8 2023-12-11 [1] CRAN (R 4.3.1)
[1] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
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